One example of an application which can make use of the classification of environment elements identified in a given environment is motion planning (or path planning). Motion planning refers in general to the determination of a route from one location to another along a set of waypoints. Motion planning is used by various mobile platforms, including, autonomous platforms (e.g. robots or UGVs-unmanned ground vehicles) and non-autonomous platforms (including various types of driven vehicles). Motion planning enables quick and safe navigation of the platform through a desired indoor or outdoor environment, including being operable in both urban and non-urban (natural) surroundings.
When determining a route, motion planning algorithms use information with respect to obstacles which are located in the traversed area and provide instructions for circumventing the obstacles. Obstacles can include for example, water reservoirs, drops in terrain, walls, holes in the ground, big rocks or any other environment element that either blocks or endangers a platform attempting to pass through an area.
In some scenarios, motion planning is executed while the platform is advancing toward its destination. In such cases, different sensing devices are utilized for obtaining real-time information with respect to a surrounding area. This information is processed to determine whether obstacles are lying in the platform's pathway and enables to suggest alternative pathways in case obstacles are detected.
Publications considered to be relevant as background to the presently disclosed subject matter are listed below. Acknowledgement of the references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter.
Colored 2D Maps for Robot Navigation with 3D Sensor Data, Oliver Wulf, Christian Brenneke, Bernardo Wagner, Institute for System Engineering, University of Hanover, Germany A navigation system for mobile service robots working in urban environments is disclosed. The system combines a 3D laser sensor with 2D algorithms for path planning and simultaneous localization and mapping (SLAM). In contrast to other map representations, the Colored 2D map is able to hold information adapted to both localization and path planning.